Kristina Brester

Weather-Based Prediction of Power Consumption in District Heating Network: Case Study in Finland

Vakhnin, Aleksei; Ryzhikov, Ivan; Brester, Christina; Niska, Harri; Kolehmainen, Mikko. 2024. Energies. 17: A1 Journal article (refereed), original research

A physical-neural network approach for residential load forecasting with dynamic load control

Nakabi, T; Brester, C; Kolehmainen, M; Niska, H. Teoksessa: (toim.) , 2023. 27th International Conference on Electricity Distribution (CIRED 2023). s. 1-5. Institution of engineering and technology A4 Conference proceedings

Automated load control detection using power quality data and machine learning

Brester, C; Hildén, A; Kolehmainen, M; Pakonen, P; Niska, H. Teoksessa: (toim.) , 2023. 27th International Conference on Electricity Distribution (CIRED 2023). s. 1-5. Institution of engineering and technology A4 Conference proceedings

Evaluating neural network models in site-specific solar PV forecasting using numerical weather prediction data and weather observations

Brester, Christina; Kallio-Myers, Viivi; Lindfors, Anders V.; Kolehmainen, Mikko; Niska, Harri. 2023. Renewable energy. 207: 266-274 A1 Journal article (refereed), original research

What is the most appropriate follow-up time for detecting the epidemiological relationship between coronary artery disease and its main risk factors: novel findings from a 35-year follow-up study

Voutilainen, Ari; Brester, Christina; Kolehmainen, Mikko; Tuomainen, Tomi-Pekka. 2023. Coronary artery disease. 34: 320-331 A1 Journal article (refereed), original research

Epidemiological analysis of coronary heart disease and its main risk factors: are their associations multiplicative, additive, or interactive?

Voutilainen, Ari; Brester, Christina; Kolehmainen, Mikko; Tuomainen, Tomi-Pekka. 2022. Annals of medicine. 54: 1500-1510 A1 Journal article (refereed), original research

Epidemiological predictive modeling: lessons learned from the Kuopio ischemic heart disease risk factor study

Brester, Christina; Voutilainen, Ari; Tuomainen, Tomi-Pekka; Kauhanen, Jussi; Kolehmainen, Mikko. 2022. Annals of epidemiology. 70: 1-8 A1 Journal article (refereed), original research

Evolutionary machine learning in epidemiological predictive modeling: examples from the Kuopio Ischemic Heart Disease Risk Factor Study

Brester, Christina. 2022. Publications of the University of Eastern Finland. Dissertations in Forestry and Natural Sciences G5 Doctoral dissertation (article)

Predicting risk of cardiovascular death in the high-dimensional cohort follow-up data in the presence of competing events: a guide for building a modeling pipeline

Brester, Christina; Tuomainen, Tomi-Pekka; Voutilainen, Ari; Kauhanen, Jussi; Kolehmainen, Mikko. 2022. Biostatistics & epidemiology. [Published online: 14 Jun 2022]: 1-15 A1 Journal article (refereed), original research

Aggregated forecasting of the load control responses using a hybrid model that combines a physically based model with machine learning

Koponen, Pekka; Salmi, Tuukka; Evens, Corentin; Takala, Suvi; Hyttinen, Antti; Brester, Christina; Kolehmainen, Mikko; Niska, Harri. Teoksessa: (toim.) , 2021. . s. 588-901. A4 Conference proceedings

Effects of data preprocessing on results of the epidemiological analysis of coronary heart disease and behaviour-related risk factors

Voutilainen, Ari; Brester, Christina; Kolehmainen, Mikko; Tuomainen, Tomi-Pekka. 2021. Annals of medicine. 53: 890-899 A1 Journal article (refereed), original research

Post-Analysis of Predictive Modeling with an Epidemiological Example

Brester, Christina; Voutilainen, Ari; Tuomainen, Tomi-Pekka; Kauhanen, Jussi; Kolehmainen, Mikko. 2021. Healthcare. 9: 792 A1 Journal article (refereed), original research

Predicting Cardiovascular Death with Automatically Designed Fuzzy Logic Rule-Based Models

Brester, Christina; Stanovov, Vladimir; Voutilainen, Ari; Tuomainen, Tomi-Pekka; Semenkin, Eugene; Kolehmainen, Mikko. Teoksessa: Merelo, Juan JuliÃ¡n; Garibaldi, Jonathan; Linares-Barranco, Alejandro; Warwick, Kevin; Madani, Kurosh(toim.) , 2021. Computational Intelligence: 11th International Joint Conference, IJCCI 2019, Vienna, Austria, September 17-19, 2019, Revised Selected Papers. s. 223-236. Springer A4 Conference proceedings

Weather-Driven Predictive Control of a Battery Storage for Improved Microgrid Resilience

Gutierrez-Rojas, Daniel; Mashlakov, Aleksei; Brester, Christina; Niska, Harri; Kolehmainen, Mikko; Narayanan, Arun; Honkapuro, Samuli; Nardelli, Pedro HJ. 2021. IEEE access. 9: 163108-163121 A1 Journal article (refereed), original research

Assessing and Comparing Short Term Load Forecasting Performance

Koponen, Pekka; Ikäheimo, Jussi; Koskela, Juha; Brester, Christina; Niska, Harri. 2020. Energies. 13: 2054 A2 Review article, Literature review, Systematic review

Nonlinear dynamic system identification with a cooperative population-based algorithm featuring a restart metaheuristic

Brester, C; Ryzhikov, I; Stanovov, V; Semenkin, E; Kolehmainen, M. Teoksessa: -(toim.) , 2020. II International Scientific Conference Advanced Technologies in Aerospace, Mechanical and Automation Engineering" - MIST: Aerospace - 2019 18-21 November 2019, Krasnoyarsk, Russia". s. 12100. A4 Conference proceedings

Potential and limitations of a pilot-scale drinking water distribution system for bacterial community predictive modelling

Brester, C; Ryzhikov, I; Siponen, S; Jayaprakash, B; Ikonen, J; Pitkänen, T; Miettinen, IT; Torvinen, E; Kolehmainen, M. 2020. Science of the total environment. 717: 137249 A1 Journal article (refereed), original research

Weather-based fault prediction in electricity networks with artificial neural networks

Brester, Christina; Niska, Harri; Ciszek, Robert ; Kolehmainen, Mikko. Teoksessa: -(toim.) , 2020. 2020 IEEE Congress on Evolutionary Computation (CEC): Conference proceedings. s. 1-8. IEEE A4 Conference proceedings

Automated toolkit for encouraging a producer to use innovative technologies in environmentally oriented economic development of mining regions

Medvedev, A; Kislyakov, I; Prokopenko, Y; Semenkina, M; Brester, K. Teoksessa: (toim.) , 2019. . s. 3020. EDP Sciences A4 Conference proceedings

Evolutionary Fuzzy Logic-based Model Design in Predicting Coronary Heart Disease and Its Progression

Brester, Christina; Stanovov, Vladimir; Voutilainen, Ari; Tuomainen, Tomi-Pekka; Semenkin Eugene; Kolehmainen, Mikko. Teoksessa: Merelo, Juan Julian; Garibaldi, Jonathan; Barranco, Alejandro Linares; Madani, Kurosh; Warwick, Kevin(toim.) , 2019. Proceedings of the 11th International Joint Conference on Computational Intelligence. s. 360-366. SCITEPRESS Science And Technology Publications A4 Conference proceedings

Multi-Objective Approach for Support Vector Machine Parameter Optimization and Variable Selection in Cardiovascular Predictive Modeling

Brester, Christina; Ryzhikov, Ivan; Tuomainen, Tomi-Pekka; Voutilainen, Ari; Semenkin, Eugene; Kolehmainen, Mikko. Teoksessa: Madani, Kurosh; Gusikhin, Oleg(toim.) , 2019. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO. s. 199-205. SCITEPRESS Science And Technology Publications A4 Conference proceedings

Restart Operator for Optimization Heuristics in Solving Linear Dynamical System Parameter Identification Problem

Ryzhikov, Ivan; Brester, Christina. Teoksessa: Merelo, Juan Julian; Garibaldi, Jonathan; Barranco, Alejandro Linares; Madani, Kurosh; Warwick, Kevin(toim.) , 2019. Proceedings of the 11th International Joint Conference on Computational Intelligence. s. 252-258. SCITEPRESS Science And Technology Publications A4 Conference proceedings

Towards the advanced predictive modelling in epidemiology

Brester, C; Tuomainen, TP; Voutilainen, A; Kauhanen, J; Semenkin, E; Kolehmainen, M. Teoksessa: (toim.) , 2019. . s. 62002. A4 Conference proceedings

Tuning Parameters of Differential Evolution: Self-adaptation, Parallel Islands, or Co-operation

Ryzhikov, Ivan; Brester, Christina. Teoksessa: Merelo, Juan Julian; Garibaldi, Jonathan; Barranco, Alejandro Linares; Madani, Kurosh; Warwick, Kevin(toim.) , 2019. Proceedings of the 11th International Joint Conference on Computational Intelligence. s. 259-264. SCITEPRESS Science And Technology Publications A4 Conference proceedings

Evolutionary methods for variable selection in the epidemiological modeling of cardiovascular diseases

Brester, Christina; Kauhanen, Jussi; Tuomainen, Tomi-Pekka; Voutilainen, Sari; Rönkkö, Mauno, Ronkainen, Kimmo; Semenkin, Eugene; Kolehmainen, Mikko. 2018. Biodata mining. 11: 18 A1 Journal article (refereed), original research

Multi-objective Evolutionary Approach in the Linear Dynamical System Inverse Modeling

Ryzhikov, Ivan; Brester, Christina; Semenkin, Eugene; Kolehmainen, Mikko. Teoksessa: Sabourin, Christophe; Merelo, Juan Julian; Linares Barranco, Alejandro; Madani, Kurosh; Warwick, Kevin(toim.) , 2018. Proceedings of the 10th International Joint Conference on Computational Intelligence - Volume 1: IJCCI. s. 281-288. SCITEPRESS Science And Technology Publications A4 Conference proceedings

Comparison of two-criterion evolutionary filtering techniques in cardiovascular predictive modelling

Brester C, Kauhanen J, Tuomainen T-P, Semenkin E, Kolehmainen M. Teoksessa: Gusikhin Oleg, Peaucelle Dimitri, Madani Kurosh(toim.) , 2016. Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics. s. 140-145. Scitepress science and technology publications A3 Book section, Chapters in research books

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Weather-Based Prediction of Power Consumption in District Heating Network: Case Study in Finland

A physical-neural network approach for residential load forecasting with dynamic load control

Automated load control detection using power quality data and machine learning

Evaluating neural network models in site-specific solar PV forecasting using numerical weather prediction data and weather observations

What is the most appropriate follow-up time for detecting the epidemiological relationship between coronary artery disease and its main risk factors: novel findings from a 35-year follow-up study

Epidemiological analysis of coronary heart disease and its main risk factors: are their associations multiplicative, additive, or interactive?

Epidemiological predictive modeling: lessons learned from the Kuopio ischemic heart disease risk factor study

Evolutionary machine learning in epidemiological predictive modeling: examples from the Kuopio Ischemic Heart Disease Risk Factor Study

Predicting risk of cardiovascular death in the high-dimensional cohort follow-up data in the presence of competing events: a guide for building a modeling pipeline

Aggregated forecasting of the load control responses using a hybrid model that combines a physically based model with machine learning

Effects of data preprocessing on results of the epidemiological analysis of coronary heart disease and behaviour-related risk factors

Post-Analysis of Predictive Modeling with an Epidemiological Example

Predicting Cardiovascular Death with Automatically Designed Fuzzy Logic Rule-Based Models

Weather-Driven Predictive Control of a Battery Storage for Improved Microgrid Resilience

Assessing and Comparing Short Term Load Forecasting Performance

Nonlinear dynamic system identification with a cooperative population-based algorithm featuring a restart metaheuristic

Potential and limitations of a pilot-scale drinking water distribution system for bacterial community predictive modelling

Weather-based fault prediction in electricity networks with artificial neural networks

Automated toolkit for encouraging a producer to use innovative technologies in environmentally oriented economic development of mining regions

Evolutionary Fuzzy Logic-based Model Design in Predicting Coronary Heart Disease and Its Progression

Multi-Objective Approach for Support Vector Machine Parameter Optimization and Variable Selection in Cardiovascular Predictive Modeling

Restart Operator for Optimization Heuristics in Solving Linear Dynamical System Parameter Identification Problem

Towards the advanced predictive modelling in epidemiology

Tuning Parameters of Differential Evolution: Self-adaptation, Parallel Islands, or Co-operation

Evolutionary methods for variable selection in the epidemiological modeling of cardiovascular diseases

Multi-objective Evolutionary Approach in the Linear Dynamical System Inverse Modeling

Comparison of two-criterion evolutionary filtering techniques in cardiovascular predictive modelling